Effects of citrus tree-shape and spraying height of small unmanned aerial vehicle on droplet distribution

被引:72
|
作者
Zhang Pan [1 ,2 ]
Deng Lie [1 ,2 ]
Lyu Qiang [1 ,2 ]
He Shaolan [1 ]
Yi Shilai [1 ]
Liu Yande [2 ]
Yu Yongxu [3 ]
Pan Haiyang [4 ]
机构
[1] Southwest Univ, Citrus Res Inst, Chongqing 400712, Peoples R China
[2] East China Jiaotong Univ, Inst Opt Elect Technol & Applicat, Nanchang 330013, Peoples R China
[3] Southwest Univ, Coll Plant Protect, Chongqing 400715, Peoples R China
[4] Zhuhai Green Guards Aviat Plant Protect Technol C, Zhuhai 519085, Guangdong, Peoples R China
关键词
citrus; tree shape; unmanned aerial vehicle (UAV); droplet deposition; DEPOSITION; QUALITY; SYSTEM; YIELD;
D O I
10.3965/j.ijabe.20160904.2178
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
In order to explore the droplet penetration of spraying with unmanned aerial vehicle (UAV) on citrus trees with different shapes, the tests were carried out at different working heights. The material was five years old Cocktail grapefruit (Citrus paradisi cv. Cocktail) grafted on Trafoliata (Poncirus trifoliata L. Raf.) and the type of UAV sprayer used was the 3W-LWS-Q60S. A solution of 300 times Ponceau 2R diluents liquid instead of pesticide was used for citrus fields spraying and the droplets were collected by paper cards. Droplets deposition parameters were extracted and analyzed using digital image processing after scanning the cards. The results showed that: 1) For the trees with round head shape canopy, the droplet depositions of the upper, middle and lower layers had a significant difference at 0.05 level. The droplet deposition had the best effect when the working height was 1.0 m, where the average droplet deposition densities were 39.97 droplets/cm(2) and the average droplet size was 0.30 mm, but the droplet coverage (3.19%) was lower than that at the working height of 1.5 m (4.27%). 2) Under three different working heights of UAV, the tree with open center shape can obtain higher droplet deposition density at all three layers than that with the round head shape canopy. It was especially prominent when the working height was 1.0 m, as the middle layer increased by 49.92%. However, the higher range of droplet deposition density meant larger fluctuation and dispersion. 3) The open center shape canopy and the 1.0 m working height obviously improved the droplet coverage rate and droplet density in the citrus plant. For these parameters of open center shape citrus tree, there was no obvious difference in the front and rear direction, but in the left and middle part of the tree crown, the difference reached a 0.05 significant level. Considering droplet deposition characteristics and the spray uniformity, the UAV performed better when working on open center shape plants at a 1.0 m working height.
引用
收藏
页码:45 / 52
页数:8
相关论文
共 45 条
  • [31] Effects of Varying Planting Patterns on Wheat Aphids' Occurrence and the Control Effect of Pesticide Reduction Spraying Process by Unmanned Aerial Vehicle
    Gao, Haifeng
    Shen, Yuyang
    Chen, Li
    Lai, Hanlin
    Yang, Hong
    Li, Guangkuo
    Zhao, Sifeng
    Ge, Feng
    APPLIED SCIENCES-BASEL, 2023, 13 (21):
  • [32] Better Droplet Deposition and Internode Shortening Effects of Plant Growth Regulator EDAH on Maize Applied by Small Unmanned Aerial Vehicle Than Electric Knapsack Sprayer
    Wang, Zhao
    Hussain, Mujahid
    Huang, Guanmin
    Yin, Jiaming
    Guo, Yuling
    Mo, You
    Duan, Liusheng
    Li, Zhaohu
    Tan, Weiming
    AGRICULTURE-BASEL, 2022, 12 (03):
  • [33] Effects of Crop Protection Unmanned Aerial System Flight Speed, Height on Effective Spraying Width, Droplet Deposition and Penetration Rate, and Control Effect Analysis on Wheat Aphids, Powdery Mildew, and Head Blight
    Zhang, Songchao
    Qiu, Baijing
    Xue, Xinyu
    Sun, Tao
    Gu, Wei
    Zhou, Fuliang
    Sun, Xiangdong
    APPLIED SCIENCES-BASEL, 2021, 11 (02): : 1 - 14
  • [34] Individual tree detection and segmentation from unmanned aerial vehicle-LiDAR data based on a trunk point distribution indicator
    Deng, Susu
    Xu, Qi
    Yue, Yuanzheng
    Jing, Sishuo
    Wang, Yixiang
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 218
  • [35] Evaluation of unmanned aerial vehicle shape, flight path and camera type for waterfowl surveys: disturbance effects and species recognition
    McEvoy, John F.
    Hall, Graham P.
    McDonald, Paul G.
    PEERJ, 2016, 4
  • [36] CFD-based Thrust Analysis of Unmanned Aerial Vehicle in Hover Mode: Effects of Single Rotor Blade Shape
    Yun, Jae Hyun
    Choi, Ha-Young
    Lee, Jongsoo
    TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS A, 2014, 38 (05) : 513 - 520
  • [37] Tree Height Estimation from Unmanned Aerial Vehicle Imagery and Its Sensitivity on Above Ground Biomass Estimation in Dry Afromontane Forest, Northern Ethiopia
    Hadush, Tigistu
    Girma, Atkilt
    Zenebe, Amanuel
    MOMONA ETHIOPIAN JOURNAL OF SCIENCE, 2021, 13 (02): : 256 - 280
  • [38] Using Small Unmanned Aerial Vehicle in 3D Modeling of Highways with Tree-Covered Roadsides to Estimate Sight Distance
    Iglesias, Luis
    De Santos-Berbel, Cesar
    Pascual, Valero
    Castro, Maria
    REMOTE SENSING, 2019, 11 (22)
  • [39] Mapping the Distribution of High-Value Broadleaf Tree Crowns through Unmanned Aerial Vehicle Image Analysis Using Deep Learning
    Htun, Nyo Me
    Owari, Toshiaki
    Tsuyuki, Satoshi
    Hiroshima, Takuya
    ALGORITHMS, 2024, 17 (02)
  • [40] Numerical simulation of downwash airflow distribution inside tree canopies of an apple orchard from a multirotor unmanned aerial vehicle (UAV) sprayer
    Zhang, Hao
    Qi, Lijun
    Wan, Junjie
    Musiu, Elizabeth M.
    Zhou, Jiarui
    Lu, Zhongao
    Wang, Pei
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2022, 195